基于全面预算管理的预算编制与审批的动态博弈

在全面预算管理体系下,重点探究预算申请与审批过程中的博弈关系,通过建立一个含不确定性因素的完全但不完美信息的动态博弈模型,找到博弈参与方决策的主要决定因素,研究怎样才能降低申请人虚报预算和审批人渎职宽审的概率,从而为这一问题的解决思路提供理论依据.     

五招拆解全面预算迷题

全面预算管理的迷题不仅仅存于目标方面，也体现在技术层面。前者包括预算目标缺乏战略研究支持、多重目标及预算目标与资源分配脱节；后者如定位不准确、强加式预算、增减预算以及缺乏有效信息系统支撑、预算控制软化严重。轻使五招，定可拆解。     

雇主-雇员博弈对人力资源共享的影响机制研究——基于所有权视角

基于所有权视角,构建了由新老雇主和雇员组成的博弈模型,并针对禀赋效应和让度效应两种所有权效应对人力资源共享的影响进行了研究。结果发现:新雇主的相对竞争力取值划分了人力资源共享博弈的状态;所有权效应增加会促进原雇主与雇员的雇佣关系,从而抑制人力资源共享形成;新雇主相对竞争力提高促进人力资源共享的形成;雇员对原雇主的成本让度应控制在阈值以内,否则会影响成本让度持续性,雇员成本让度具有收益导向特性。因此量力选择共享合作企业,适度引导所有权效应,将推进企业间人力资源的互利共享。     

企业资本预算中的风险补偿与资本配置效率研究

在分权化企业的资本预算中，由于存在着分部管理者的道德风险与风险规避偏好，总部管理者必须对包含风险补偿的激励成本与激励努力带来的预期收益两者进行权衡。当努力导致的收益介于最优激励成本与风险规避偏好导致的次优激励成本之间时，风险补偿的存在将会导致总部管理者降低激励努力水平，从而减少了投资的期望收益，降低了资本的配置效率。     

海航预算新干线

作为一家多元化的现代企业集团,海航拥有现代化的管理思想和方法。早在多年前,海航就已将预算管理纳入了管理体系,并于2008年引入了预算信息系统。     

计数型最小样本量截尾值的序贯检验

对具有"高成本、破坏性"计数型产品的可靠性验收试验,序贯检验方案的样本量截尾值对试验的成本预算起着决定性作用.为降低试验的成本预算,本文对最小样本量截尾值序贯检验(minimum truncated sample size sequential test, MTST)进行研究,给出MTST的定义、性质及求解方法.通过与目前广泛采用的国际标准IEC1123及序贯网图检验进行比较,结果表明MTST显著地减少了样本量截尾值.为进一步减少序贯检验的样本量截尾值,当已知产品质量的先验信息时,本文研究了Bayes最小样本量截尾值序贯检验方案(Bayesian minimum truncated sample size sequential test, BMTST),与MTST的比较表明, BMTST极大地减少了序贯检验的样本量截尾值及平均试验次数,能更好地缩减"高成本、破坏性"产品的试验成本预算及平均试验费用.     

油企成本战——探寻油企过冬期成本方程式：智慧成本演进

近年来我国现代服务业快速发展,高科技石油服务企业凭借明显区别于传统石油行业的利润模式成为一个典型群落,尤其是其中的8家中小板和创业板上市公司更是行业发展的标杆。值得注意的是,这些高科技石油服务企业成本管理体系仍遵循我国现行成本管理体系的理念与执行方式,而利润模式变化引起的成本动因急需成本管理的创新跟进。     

NEC成本进化记

精细化成本预算管理，无论是在衰退、低迷还是复苏、繁荣阶段，都发挥着关键作用。     

交通产业链上企业工程项目成本控制的影响因素研究

一些企业以轨道交通产业为纽带形成了交通产业链，轨道交通产业链上的企业要注重对相关工程项目实施全过程中的成本控制.从产业链的视角出发，围绕财务指标、内部业务流程指标、客户指标、学习与成长能力指标这4个方面，构建了评价指标体系和成本控制指标体系.运用层次分析法和模糊综合评价法进行评价和分析，找出了影响轨道交通产业链上企业工程项目成本控制的主要因素.研究表明，有55%的人认为财务指标、内部业务流程指标、客户指标、学习与成长能力指标这4个因素对轨道交通工程项目成本控制的影响较大.     

制造企业的预算蓝本

全面预算作为西方先进的管理理念引进中国企业后,由于理解偏差与执行不力,已降格成为成本费用控制的工具,失去了自身应有的精髓,无法建立起有效的全面管控体系。鉴于实际工作中出现的问题,笔者以一家从事机械设备开发、生产、营销与服务的上市公司-LZ集团为研究蓝本,着重将平衡计分卡引入全面预算管理,通过实证研究,设计出两者贴合的战略行动方案。     

Helping Managers Manage

Do conventional management accounts help managers manage? This paper argues that the answer to this question is ‘No’, primarily because conventionally prepared budgets are not accepted by managers as valid measures of performance as a result of either forecasting errors in the data used in the original budget or weaknesses in the simulation algorithms inherent in the budget. The paper then suggests that management accounts can be made more meaningful by incorporating within the management accounting system a ‘resource management system’, the basis of which is a powerful simulation model.     

Optimal preventive maintenance policy for electric power distribution systems based on the fuzzy AHP methods

In power distribution systems, with their great vastness and various outage causes, one of the most important problems of power distribution companies is to select a suitable maintenance strategy of system elements and method of financial planning for the maintenance of system elements with the two objectives of decrease in outage costs and improvement of system reliability. In this article, a practical method is introduced for the selection of a suitable system elements maintenance strategy; moreover, to plan the preventive maintenance budget for the system elements, two methods are offered: the cost optimization method and the fuzzy Analytic Hierarchy Process (AHP) method. In the former method, a new model of system maintenance cost is offered. This model, based on system outage information, the elements maintenance costs are determined as functions of system reliability indices and preventive maintenance budget. The latter method, too, a new guideline is introduced for considering the cost and reliability criteria in the trend of preventive maintenance budget planning. In this method, the preventive maintenance budget for the elements is determined based on relative priority of elements with reliability criteria. © 2015 Wiley Periodicals, Inc. Complexity 21: 70–88, 2016     

Multi-criteria approximation schemes for the resource constrained shortest path problem

In the resource constrained shortest path problem we are given a directed graph along with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements from a set of resources with finite budget limits. A minimum cost source-destination path is sought such that the total consumption of the arcs from each resource does not exceed its budget limit. In the case of constant number of weight functions we give a fully polynomial time multi-criteria approximation scheme for the problem which returns a source-destination path of cost at most the optimum, however, the path may slightly violate the budget limits. On the negative side, we show that there does not exist a polynomial time multi-criteria approximation scheme for the problem if the number of weight functions is not a constant. The latter result applies to a broad class of problems as well, including the multi-dimensional knapsack, the multi-budgeted spanning tree, the multi-budgeted matroid basis and the multi-budgeted bipartite perfect matching problems.     

A MIXED CONTROL PROBLEM OF THE MANAGEMENT OF NATURAL RESOURCES

In this paper, we study the optimal solutions of a model of natural resource management which allows for both impulse and continuous harvesting policies. This type of model is known in the literature as mixed optimal control problem. In the resource management context, each type of control represents a different harvesting technology, which has a different cost. In particular, we want to know when the following conjecture made by Clark is an optimal solution to this mixed optimal control problem: if the harvesting capacity is unlimited, it is optimal to jump immediately to the steady state of the continuous time problem and then to stay there. We show that under a particular relationship between the continuous and the impulse profit function, the conjecture made by Clark is true. In other cases, however, it is either better to use only continuous control variables or to jump to resource levels which are smaller than the steady state and then let the resource grow back to the steady state. These results emphasize the importance of the cost functions in the modeling of natural resource management.     

基于需求的实时网络定价策略

价格作为一种网络拥塞控制管理与资源分配的机制不断地表现出较高的效率。基于对网络使用实际流量的信息，本提出了一种实时的网络定价策略——基于需求的实时网络定价策略。该定价策略由三部分构成：固定连接费、资源使用费及网络拥塞费。与传统的定价策略相比，基于需求的实时网络定价策略更能反映实际的需求情况，在网络拥塞控制管理与网络资源分配等方面有更高的效率。     

Optimal control of dengue epidemic outbreaks under limited resources

In this paper, we reflect upon control intervention practices habitually exerted by healthcare authorities in tropical areas that suffer from incidental outbreaks of dengue fever, in particular, the city of Cali, Colombia. Such control interventions, principally based on the insecticide spraying, are carried out sporadically in order to overcome an ongoing epidemic or at least to reduce its size. It is worth pointing out that control actions of this type do not usually account for sufficient budget because epidemic outbreaks are difficult to predict. In practical terms, these occasional control interventions are performed by spraying, as quickly as possible, all existing stock of insecticide (regardless of its lethality) and employing all available manpower. The goal of this paper is to design better strategies for insecticide-based control actions, which are capable of preventing more human infections at no additional cost, and to reveal the obsolescence of current vector eradication practices. Our approach relies on dynamic optimization, where the number of averted human infections is maximized under budget constraint and subject to a simple dengue transmission model amended with one control variable that stands for the insecticide spraying. As a result, we obtain structurally robust control intervention policies that demonstrate better performance and higher resilience to possible budget limitations than traditional modus operandi.     

Implementation of goal programmingin long-range resource planning in university management

This paper presents a resource allocation model via Goal Programming (GP) in a long-range planning horizon in university management. In the proposed model, the introduction of new courses in the academic units and the allocation of available budget within the academic units as well as the forecast of the budget which is actually needed for better academic performance are taken into consideration. An illustrative example is presented to expound the model     

A note on issues of over-conservatism in robust optimization with cost uncertainty

We identify and discuss issues of hidden over-conservatism in robust linear optimization, when the uncertainty set is polyhedral with a budget of uncertainty constraint. The decision-maker selects the budget of uncertainty to reflect his degree of risk aversion, i.e. the maximum number of uncertain parameters that can take their worst-case value. In the first setting, the cost coefficients of the linear programming problem are uncertain, as is the case in portfolio management with random stock returns. We provide an example where, for moderate values of the budget, the optimal solution becomes independent of the nominal values of the parameters, i.e. is completely disconnected from its nominal counterpart, and discuss why this happens. The second setting focusses on linear optimization with uncertain upper bounds on the decision variables, which has applications in revenue management with uncertain demand and can be rewritten as a piecewise linear problem with cost uncertainty. We show in an example that it is possible to have more demand parameters equal their worst-case value than what is allowed by the budget of uncertainty, although the robust formulation is correct. We explain this apparent paradox.     

The effect of human agent in project management

The article deals with the effect of a human agent on the activity realization in a project. It does so from the perspective of the Theory of Constraints where the weakest point is the deadline of partial activity. Every existing activity in any project is, to a higher or lower extent, determined by the effect of the human agent. The inefficiency of a number of projects in practice is largely caused by an unsuccessful realization of partial activities. The effect of the human agent is in this respect fundamental. The human agent, as an allocated resource in the activity, is liable to a number of non-specified impacts and stimuli, and as such s/he is rather versatile in his/her behaviour. The versatility of the human agent in projects can be described by the “Student Syndrome” phenomenon and by the first “Parkinson’s law”. Both these qualitative phenomena create a starting point for the introduced theoretical and quantitative research. The findings in this article are based on the set of real data of work effort of the students of daily study programme on one university in the Czech Republic. The article presents, as the authors’ own theoretical contribution, a mathematical model for the “Student Syndrome” phenomenon with a practical use in quantitative methods of project management. This model was derived analytically from a performed data analysis and we can assume that it will be useful for further theoretical development of quantitative methods in project management. In the article we deduce the theoretical differentiation of the “Student Syndrome” phenomenon in work effort into three terminable phases during three different types of resource work allocation. We can regard this original viewpoint as suggestive for the area of human resources management in projects. Its contribution lies in delimitation of time-targeted resource stimulation, which may lead to lower project costs, besides higher work efficiency and compliance with time-targeted deadlines of activity termination. The article brings the quantification of qualitative features of the human agent in project management.     

Branch and bound based solution algorithms for the budget constrained discrete time/cost trade-off problem

The time/cost trade-off models in project management aim to reduce the project completion time by putting extra resources on activity durations. The budget problem in discrete time/cost trade-off scheduling selects a time/cost mode for each activity so as to minimize the project completion time without exceeding the available budget. There may be alternative modes that solve the budget problem optimally and each solution may have a different total cost value. In this study we consider the budget problem and aim to find the minimum cost solution among the minimum project completion time solutions. We analyse the structure of the problem together with its linear programming relaxation and derive some mechanisms for reducing the problem size. We solve the reduced problem by branch and bound based optimization and heuristic algorithms. We find that our branch and bound algorithm finds optimal solutions for medium-sized problem instances in reasonable times and the heuristic algorithms produce high quality solutions very quickly.